World Economic Data

Group TTE

Members: Tyler David, Tony Lu, Eric Laigaie

In this project, we will be visualizing data on economic statistics by country. These statistics include: Inequality, Inflation, Poverty, Wage Gap, Social Mobility, and Unemployment. This data is visualized through choropleths and bar charts. Additionally, a table view is included to give the user an easy tool when combing through the data.

import altair as alt
import pandas as pd
import numpy as np
from shapely import wkt
!pip install pipwin
!pip install panel
!pipwin install numpy
!pipwin install pandas
!pipwin install shapely
!pipwin install geopandas
import geopandas as gpd
import panel as pn
pn.extension('vega')

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  File "c:\users\ericl\anaconda3\lib\runpy.py", line 194, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "c:\users\ericl\anaconda3\lib\runpy.py", line 87, in _run_code
    exec(code, run_globals)
  File "C:\Users\ericl\anaconda3\Scripts\pipwin.exe\__main__.py", line 7, in <module>
  File "c:\users\ericl\anaconda3\lib\site-packages\pipwin\command.py", line 103, in main
    cache.install(package)
  File "c:\users\ericl\anaconda3\lib\site-packages\pipwin\pipwin.py", line 300, in install
    wheel_file = self.download(requirement)
  File "c:\users\ericl\anaconda3\lib\site-packages\pipwin\pipwin.py", line 294, in download
    return self._download(requirement, dest)
  File "c:\users\ericl\anaconda3\lib\site-packages\pipwin\pipwin.py", line 290, in _download
    obj.start()
  File "c:\users\ericl\anaconda3\lib\site-packages\pySmartDL\pySmartDL.py", line 267, in start
    urlObj = urllib.request.urlopen(req, timeout=self.timeout, context=self.context)
  File "c:\users\ericl\anaconda3\lib\urllib\request.py", line 222, in urlopen
    return opener.open(url, data, timeout)
  File "c:\users\ericl\anaconda3\lib\urllib\request.py", line 531, in open
    response = meth(req, response)
  File "c:\users\ericl\anaconda3\lib\urllib\request.py", line 640, in http_response
    response = self.parent.error(
  File "c:\users\ericl\anaconda3\lib\urllib\request.py", line 569, in error
    return self._call_chain(*args)
  File "c:\users\ericl\anaconda3\lib\urllib\request.py", line 502, in _call_chain
    result = func(*args)
  File "c:\users\ericl\anaconda3\lib\urllib\request.py", line 649, in http_error_default
    raise HTTPError(req.full_url, code, msg, hdrs, fp)
urllib.error.HTTPError: HTTP Error 404: Not Found

Package `pandas` found in cache
Downloading package . . .
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Traceback (most recent call last):
  File "c:\users\ericl\anaconda3\lib\runpy.py", line 194, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "c:\users\ericl\anaconda3\lib\runpy.py", line 87, in _run_code
    exec(code, run_globals)
  File "C:\Users\ericl\anaconda3\Scripts\pipwin.exe\__main__.py", line 7, in <module>
  File "c:\users\ericl\anaconda3\lib\site-packages\pipwin\command.py", line 103, in main
    cache.install(package)
  File "c:\users\ericl\anaconda3\lib\site-packages\pipwin\pipwin.py", line 300, in install
    wheel_file = self.download(requirement)
  File "c:\users\ericl\anaconda3\lib\site-packages\pipwin\pipwin.py", line 294, in download
    return self._download(requirement, dest)
  File "c:\users\ericl\anaconda3\lib\site-packages\pipwin\pipwin.py", line 290, in _download
    obj.start()
  File "c:\users\ericl\anaconda3\lib\site-packages\pySmartDL\pySmartDL.py", line 267, in start
    urlObj = urllib.request.urlopen(req, timeout=self.timeout, context=self.context)
  File "c:\users\ericl\anaconda3\lib\urllib\request.py", line 222, in urlopen
    return opener.open(url, data, timeout)
  File "c:\users\ericl\anaconda3\lib\urllib\request.py", line 531, in open
    response = meth(req, response)
  File "c:\users\ericl\anaconda3\lib\urllib\request.py", line 640, in http_response
    response = self.parent.error(
  File "c:\users\ericl\anaconda3\lib\urllib\request.py", line 569, in error
    return self._call_chain(*args)
  File "c:\users\ericl\anaconda3\lib\urllib\request.py", line 502, in _call_chain
    result = func(*args)
  File "c:\users\ericl\anaconda3\lib\urllib\request.py", line 649, in http_error_default
    raise HTTPError(req.full_url, code, msg, hdrs, fp)
urllib.error.HTTPError: HTTP Error 404: Not Found

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country_data = pd.read_csv('data_viz_final_project_data.csv')
country_data['geometry'] = country_data['geometry'].apply(wkt.loads)
country_data = gpd.GeoDataFrame(country_data, crs='epsg:4326')

The next 6 cells are generating the charts used below.

continents = ['Africa', 'Asia', 'Europe', 'North America', 'South America', 'Oceania']

continent_radio = alt.binding_radio(options=continents)

continent_select = alt.selection_single(fields=['continent'], bind=continent_radio, name="continent")
continent_color_condition = alt.condition(continent_select,
                      alt.Color('continent:N', legend=None),
                      alt.value('lightgray'))


base = alt.Chart(country_data).mark_geoshape(invalid=None).encode(
    color=alt.condition('datum.unemployment !== null', 'unemployment:Q', alt.value('lightgray')),
    tooltip=['name', 'unemployment']
).project(type='albers').properties(
    width=800,
    height=600
).transform_filter(
    continent_select
).project(
    'equirectangular'
).properties(
    width=500,
    height=300
)

highlight_continent = base.add_selection(
    continent_select
).encode(
    color=continent_color_condition
).properties(title="Unemployment Choropleth")

filtered_une = country_data[pd.isna(country_data['unemployment']) == False]
bar = alt.Chart(filtered_une).mark_bar(invalid=None).encode(
    y = alt.Y('unemployment:Q', axis=alt.Axis(format='%', title='Unemployment')),
    x = alt.X('name', sort='-y'),
    color = 'continent',
    tooltip = ['name', 'unemployment']
).properties(title='Unemployment Bar Chart')
mean = alt.Chart(filtered_une).mark_rule(color='black', size=3).encode(
    y='mean(unemployment):Q'
)
median = alt.Chart(filtered_une).mark_rule(color='gray', size=3).encode(
    y='median(unemployment):Q'
)

unemployment_chart = highlight_continent + base | (bar + mean + median)

continents = ['Africa', 'Asia', 'Europe', 'North America', 'South America', 'Oceania']

continent_radio = alt.binding_radio(options=continents)

continent_select = alt.selection_single(fields=['continent'], bind=continent_radio, name="continent")
continent_color_condition = alt.condition(continent_select,
                      alt.Color('continent:N', legend=None),
                      alt.value('lightgray'))


base = alt.Chart(country_data).mark_geoshape(invalid=None).encode(
    color=alt.condition('datum.newinflation !== null', 'newinflation:Q', alt.value('lightgray')),
    tooltip=['name', 'inflation']
).project(type='albers').properties(
    width=800,
    height=600
).transform_filter(
    continent_select
).project(
    'equirectangular'
).properties(
    width=500,
    height=300
)

highlight_continent = base.add_selection(
    continent_select
).encode(
    color=continent_color_condition
).properties(title="Inflation Choropleth")

filtered_inf = country_data[pd.isna(country_data['inflation']) == False]
bar = alt.Chart(filtered_inf).mark_bar(invalid=None).encode(
    y = alt.Y('inflation:Q', axis=alt.Axis(format='%', title='Inflation')),
    x = alt.X('name', sort='-y'),
    color = 'continent',
    tooltip = ['name', 'inflation']
).properties(title='Inflation Bar Chart')
mean = alt.Chart(filtered_inf).mark_rule(color='black', size=3).encode(
    y='mean(inflation):Q'
)
median = alt.Chart(filtered_inf).mark_rule(color='gray', size=3).encode(
    y='median(inflation):Q'
)

inflation_chart = highlight_continent + base | (bar + mean + median)

continents = ['Africa', 'Asia', 'Europe', 'North America', 'South America', 'Oceania']

continent_radio = alt.binding_radio(options=continents)

continent_select = alt.selection_single(fields=['continent'], bind=continent_radio, name="continent")
continent_color_condition = alt.condition(continent_select,
                      alt.Color('continent:N', legend=None),
                      alt.value('lightgray'))


base = alt.Chart(country_data).mark_geoshape(invalid=None).encode(
    color=alt.condition('datum.wage_gap !== null', 'wage_gap:Q', alt.value('lightgray')),
    tooltip=['name', 'wage_gap']
).project(type='albers').properties(
    width=800,
    height=600
).transform_filter(
    continent_select
).project(
    'equirectangular'
).properties(
    width=500,
    height=300
)

highlight_continent = base.add_selection(
    continent_select
).encode(
    color=continent_color_condition
).properties(title="Wage Gap Choropleth")


filtered_wag = country_data[pd.isna(country_data['wage_gap']) == False]
bar = alt.Chart(filtered_wag).mark_bar(invalid=None).encode(
    y = alt.Y('wage_gap:Q', axis=alt.Axis(format='%', title='Wage Gap')),
    x = alt.X('name', sort='-y'),
    color = 'continent',
    tooltip = ['name', 'wage_gap']
).properties(title='Wage Gap Bar Chart')
mean = alt.Chart(filtered_wag).mark_rule(color='black', size=3).encode(
    y='mean(wage_gap):Q'
)
median = alt.Chart(filtered_wag).mark_rule(color='gray', size=3).encode(
    y='median(wage_gap):Q'
)

wage_gap_chart = highlight_continent + base | (bar + mean + median)

continents = ['Africa', 'Asia', 'Europe', 'North America', 'South America', 'Oceania']

continent_radio = alt.binding_radio(options=continents)

continent_select = alt.selection_single(fields=['continent'], bind=continent_radio, name="continent")
continent_color_condition = alt.condition(continent_select,
                      alt.Color('continent:N', legend=None),
                      alt.value('lightgray'))


base = alt.Chart(country_data).mark_geoshape(invalid=None).encode(
    color=alt.condition('datum.social_mobility !== null', 'social_mobility:Q', alt.value('lightgray')),
    tooltip=['name', 'social_mobility']
).project(type='albers').properties(
    width=800,
    height=600
).transform_filter(
    continent_select
).project(
    'equirectangular'
).properties(
    width=500,
    height=300
)

highlight_continent = base.add_selection(
    continent_select
).encode(
    color=continent_color_condition
).properties(title="Social Mobility Choropleth")

filtered_soc = country_data[pd.isna(country_data['social_mobility']) == False]
bar = alt.Chart(filtered_soc).mark_bar(invalid=None).encode(
    y = alt.Y('social_mobility:Q', axis=alt.Axis(title='Social Mobility')),
    x = alt.X('name', sort='-y'),
    color = 'continent',
    tooltip = ['name', 'social_mobility']
).properties(title='Social Mobility Bar Chart')
mean = alt.Chart(filtered_soc).mark_rule(color='black', size=3).encode(
    y='mean(social_mobility):Q'
)
median = alt.Chart(filtered_soc).mark_rule(color='gray', size=3).encode(
    y='median(social_mobility):Q'
)

social_mobility_chart = highlight_continent + base | (bar + mean + median)

continents = ['Africa', 'Asia', 'Europe', 'North America', 'South America', 'Oceania']

continent_radio = alt.binding_radio(options=continents)

continent_select = alt.selection_single(fields=['continent'], bind=continent_radio, name="continent")
continent_color_condition = alt.condition(continent_select,
                      alt.Color('continent:N', legend=None),
                      alt.value('lightgray'))


base = alt.Chart(country_data).mark_geoshape(invalid=None).encode(
    color=alt.condition('datum.poverty !== null', 'poverty:Q', alt.value('lightgray')),
    tooltip=['name', 'poverty']
).project(type='albers').properties(
    width=800,
    height=600
).transform_filter(
    continent_select
).project(
    'equirectangular'
).properties(
    width=500,
    height=300
)

highlight_continent = base.add_selection(
    continent_select
).encode(
    color=continent_color_condition
).properties(title="Poverty Choropleth")

filtered_pov = country_data[pd.isna(country_data['poverty']) == False]
bar = alt.Chart(filtered_pov).mark_bar(invalid=None).encode(
    y = alt.Y('poverty:Q', axis=alt.Axis(format='%', title='Poverty')),
    x = alt.X('name', sort='-y'),
    color = 'continent',
    tooltip = ['name', 'poverty']
).properties(title='Poverty Bar Chart')
mean = alt.Chart(filtered_pov).mark_rule(color='black', size=3).encode(
    y='mean(poverty):Q'
)
median = alt.Chart(filtered_pov).mark_rule(color='gray', size=3).encode(
    y='median(poverty):Q'
)

poverty_chart = highlight_continent + base | (bar + mean + median)

continents = ['Africa', 'Asia', 'Europe', 'North America', 'South America', 'Oceania']

continent_radio = alt.binding_radio(options=continents)

continent_select = alt.selection_single(fields=['continent'], bind=continent_radio, name="continent")
continent_color_condition = alt.condition(continent_select,
                      alt.Color('continent:N', legend=None),
                      alt.value('lightgray'))


base = alt.Chart(country_data).mark_geoshape(invalid=None).encode(
    color=alt.condition('datum.inequality !== null', 'inequality:Q', alt.value('lightgray')),
    tooltip=['name', 'inequality']
).project(type='albers').properties(
    width=800,
    height=600
).transform_filter(
    continent_select
).project(
    'equirectangular'
).properties(
    width=500,
    height=300
)

highlight_continent = base.add_selection(
    continent_select
).encode(
    color=continent_color_condition
).properties(title="Inequality Choropleth")

filtered_ine = country_data[pd.isna(country_data['inequality']) == False]
bar = alt.Chart(filtered_ine).mark_bar(invalid=None).encode(
    y = alt.Y('inequality:Q', axis=alt.Axis(title='Inequality')),
    x = alt.X('name', sort='-y'),
    color = 'continent',
    tooltip = ['name', 'inequality']
).properties(title='Inequality Bar Chart')
mean = alt.Chart(filtered_ine).mark_rule(color='black',size=3).encode(
    y='mean(inequality):Q'
)
median = alt.Chart(filtered_ine).mark_rule(color='gray', size=3).encode(
    y='median(inequality):Q'
)

inequality_chart = ((highlight_continent + base) | (bar + mean + median))

Panel tabs are created and displayed

tabs = pn.Tabs()
tabs.append(('Wage Gap',wage_gap_chart))
tabs.append(('Unemployment', unemployment_chart))
tabs.append(('Social Mobility', social_mobility_chart))
tabs.append(('Inflation',inflation_chart))
tabs.append(('Poverty', poverty_chart))
tabs.append(('Inequality', inequality_chart))
tabs

from ipywidgets import widgets
from IPython.display import display
pd.set_option("display.max_rows", None, "display.max_columns", None)

Table view is created: Users can filter by Country, Continent, or Statistic

table_data = country_data.copy()
table_data = table_data.drop(columns=['newinflation', 'geometry'])

#filter by country
def country_func(Country):
    if Country=='All':
        display(table_data)
    else:
        display(table_data[table_data['name'] == Country])

country_options = table_data['name'].tolist()
country_options.insert(0, 'All')

country_select =  widgets.Select(options=country_options)

country_filter = widgets.interactive(country_func, Country=country_select)

#filter by continent
def cont_select(Continent):
    if Continent=='All':
        display(table_data)
    else:
        display(table_data[table_data['continent'] == Continent])

continent_options = ['All', 'Africa', 'Asia', 'Europe', 'North America', 'Oceania', 'South America']

continent_select =  widgets.Select(options=continent_options)

continent_filter = widgets.interactive(cont_select, Continent=continent_select)

table = pn.Tabs()
table.append(('Filter by Country', country_filter))
table.append(('Filter by Continent', continent_filter))
table

full = pn.Tabs()
full.append(('Maps', tabs))
full.append(('Tables', table))
full

For the slider, we have to figure out how to relay the slider bounds once the cell is run and everytime the user picks something in the dropdown. Not sure how to do that.

#filter by statistic with slider
stat_options = ['All', 'inflation', 'inequality', 'social_mobility', 'poverty', 'unemployment', 'wage_gap']
stat_slider = widgets.IntSlider(min=0, max=100, step=1, value=0)
stat_select =  widgets.Select(options=stat_options)

 
def update_c_range(*args):
    if stat_select.value=='All':
        stat_slider.max = 100
    else:
        stat_slider.max = table_data[stat_select.value].max()
        stat_slider.min = table_data[stat_select.value].min()
        stat_slider.step = .01
        stat_slider.value = 0

stat_select.observe(update_c_range, 'value')
 
def view3(Statistic, Slider):
    if Statistic=='All':
        display(table_data)
    else:
        display(table_data[table_data[Statistic] >= Slider])

widgets.interactive(view3,Statistic=stat_select,Slider=stat_slider)

---------------------------------------------------------------------------
TraitError                                Traceback (most recent call last)
~\anaconda3\lib\site-packages\ipywidgets\widgets\widget.py in _handle_msg(self, msg)
    674                 if 'buffer_paths' in data:
    675                     _put_buffers(state, data['buffer_paths'], msg['buffers'])
--> 676                 self.set_state(state)
    677 
    678         # Handle a state request.

~\anaconda3\lib\site-packages\ipywidgets\widgets\widget.py in set_state(self, sync_data)
    543                     from_json = self.trait_metadata(name, 'from_json',
    544                                                     self._trait_from_json)
--> 545                     self.set_trait(name, from_json(sync_data[name], self))
    546 
    547     def send(self, content, buffers=None):

~\anaconda3\lib\contextlib.py in __exit__(self, type, value, traceback)
    118         if type is None:
    119             try:
--> 120                 next(self.gen)
    121             except StopIteration:
    122                 return False

~\anaconda3\lib\site-packages\traitlets\traitlets.py in hold_trait_notifications(self)
   1212                 for changes in cache.values():
   1213                     for change in changes:
-> 1214                         self.notify_change(change)
   1215 
   1216     def _notify_trait(self, name, old_value, new_value):

~\anaconda3\lib\site-packages\ipywidgets\widgets\widget.py in notify_change(self, change)
    604                 # Send new state to front-end
    605                 self.send_state(key=name)
--> 606         super(Widget, self).notify_change(change)
    607 
    608     def __repr__(self):

~\anaconda3\lib\site-packages\traitlets\traitlets.py in notify_change(self, change)
   1225     def notify_change(self, change):
   1226         """Notify observers of a change event"""
-> 1227         return self._notify_observers(change)
   1228 
   1229     def _notify_observers(self, event):

~\anaconda3\lib\site-packages\traitlets\traitlets.py in _notify_observers(self, event)
   1262                 c = getattr(self, c.name)
   1263 
-> 1264             c(event)
   1265 
   1266     def _add_notifiers(self, handler, name, type):

~\anaconda3\lib\site-packages\ipywidgets\widgets\widget_selection.py in _propagate_index(self, change)
    233             self.label = label
    234         if self.value is not value:
--> 235             self.value = value
    236 
    237     @validate('value')

~\anaconda3\lib\site-packages\traitlets\traitlets.py in __set__(self, obj, value)
    602             raise TraitError('The "%s" trait is read-only.' % self.name)
    603         else:
--> 604             self.set(obj, value)
    605 
    606     def _validate(self, obj, value):

~\anaconda3\lib\site-packages\traitlets\traitlets.py in set(self, obj, value)
    591             # we explicitly compare silent to True just in case the equality
    592             # comparison above returns something other than True/False
--> 593             obj._notify_trait(self.name, old_value, new_value)
    594 
    595     def __set__(self, obj, value):

~\anaconda3\lib\site-packages\traitlets\traitlets.py in _notify_trait(self, name, old_value, new_value)
   1215 
   1216     def _notify_trait(self, name, old_value, new_value):
-> 1217         self.notify_change(Bunch(
   1218             name=name,
   1219             old=old_value,

~\anaconda3\lib\site-packages\ipywidgets\widgets\widget.py in notify_change(self, change)
    604                 # Send new state to front-end
    605                 self.send_state(key=name)
--> 606         super(Widget, self).notify_change(change)
    607 
    608     def __repr__(self):

~\anaconda3\lib\site-packages\traitlets\traitlets.py in notify_change(self, change)
   1225     def notify_change(self, change):
   1226         """Notify observers of a change event"""
-> 1227         return self._notify_observers(change)
   1228 
   1229     def _notify_observers(self, event):

~\anaconda3\lib\site-packages\traitlets\traitlets.py in _notify_observers(self, event)
   1262                 c = getattr(self, c.name)
   1263 
-> 1264             c(event)
   1265 
   1266     def _add_notifiers(self, handler, name, type):

<ipython-input-201-03e33554b2e1> in update_c_range(*args)
      9         stat_slider.max = 100
     10     else:
---> 11         stat_slider.max = table_data[stat_select.value].max()
     12         stat_slider.min = table_data[stat_select.value].min()
     13         stat_slider.step = .01

~\anaconda3\lib\site-packages\traitlets\traitlets.py in __set__(self, obj, value)
    602             raise TraitError('The "%s" trait is read-only.' % self.name)
    603         else:
--> 604             self.set(obj, value)
    605 
    606     def _validate(self, obj, value):

~\anaconda3\lib\site-packages\traitlets\traitlets.py in set(self, obj, value)
    576 
    577     def set(self, obj, value):
--> 578         new_value = self._validate(obj, value)
    579         try:
    580             old_value = obj._trait_values[self.name]

~\anaconda3\lib\site-packages\traitlets\traitlets.py in _validate(self, obj, value)
    610             value = self.validate(obj, value)
    611         if obj._cross_validation_lock is False:
--> 612             value = self._cross_validate(obj, value)
    613         return value
    614 

~\anaconda3\lib\site-packages\traitlets\traitlets.py in _cross_validate(self, obj, value)
    616         if self.name in obj._trait_validators:
    617             proposal = Bunch({'trait': self, 'value': value, 'owner': obj})
--> 618             value = obj._trait_validators[self.name](obj, proposal)
    619         elif hasattr(obj, '_%s_validate' % self.name):
    620             meth_name = '_%s_validate' % self.name

~\anaconda3\lib\site-packages\traitlets\traitlets.py in __call__(self, *args, **kwargs)
    973         """Pass `*args` and `**kwargs` to the handler's function if it exists."""
    974         if hasattr(self, 'func'):
--> 975             return self.func(*args, **kwargs)
    976         else:
    977             return self._init_call(*args, **kwargs)

~\anaconda3\lib\site-packages\ipywidgets\widgets\widget_int.py in _validate_max(self, proposal)
    116         max = proposal['value']
    117         if max < self.min:
--> 118             raise TraitError('setting max < min')
    119         if max < self.value:
    120             self.value = max

TraitError: setting max < min

Everything past here doesn't work as well as the cells above.

select_country = widgets.Dropdown(
 options=country_data['name'],
 value='Afghanistan',
 rows=len(country_data),
 description='Country:'
 )
    
selecter = display(select_country)

button_country = widgets.Button(description='Display DataFrame')
display(button_country)

def button_click(b, select_country):
    display(country_data[country_data['name'] == select_country])

button_country.on_click(button_click(0, select_country.value))

	name	continent	inequality	wage_gap	social_mobility	poverty	newinflation	inflation	unemployment	geometry
0	Afghanistan	Asia	NaN	NaN	NaN	NaN	2.3	2.3	11.7	POLYGON ((61.21082 35.65007, 62.23065 35.27066...

sel = widgets.Dropdown(
 options=['inflation', 'inequality', 'wage_gap', 'social_mobility', 'poverty', 'unemployment'],
 value='inflation',
 rows=6,
 description='Statistic:'
 )
display(sel)

button = widgets.Button(description='Display DataFrame')
display(button)

def button_click(b, sel):
    display(country_data[['name', sel]])

button.on_click(button_click(0, sel.value))

	name	inflation
0	Afghanistan	2.3
1	Albania	1.4
2	Algeria	2.0
3	Angola	17.1
4	Argentina	NaN
5	Armenia	1.4
6	Australia	1.6
7	Austria	1.5
8	Azerbaijan	2.6
9	Bahamas, The	2.5
10	Bangladesh	5.6
11	Belarus	5.6
12	Belgium	1.4
13	Belize	NaN
14	Benin	-0.9
15	Bhutan	2.7
16	Bolivia	1.8
17	Bosnia and Herzegovina	0.6
18	Botswana	2.8
19	Brazil	3.7
20	Brunei	-0.4
21	Bulgaria	3.1
22	Burkina Faso	3.1
23	Burundi	-0.7
24	Cambodia	2.5
25	Cameroon	2.5
26	Canada	1.9
27	Central African Republic	NaN
28	Chad	-1.0
29	Chile	2.6
30	China	2.9
31	Colombia	3.5
32	Costa Rica	2.1
33	Croatia	0.8
34	Cuba	NaN
35	Cyprus	0.3
36	Czech Republic	2.8
37	Democratic Republic of Congo	2.9
38	Denmark	0.8
39	Djibouti	3.3
40	Dominican Republic	1.8
41	Ecuador	0.3
42	Egypt	14.4
43	El Salvador	0.1
44	Equatorial Guinea	1.2
45	Eritrea	NaN
46	Estonia	2.3
47	Eswatini	2.6
48	Ethiopia	15.8
49	Fiji	1.8
50	Finland	1.0
51	France	1.1
52	Gabon	2.5
53	Gambia, The	7.1
54	Georgia	4.9
55	Germany	1.4
56	Ghana	7.2
57	Greece	0.3
58	Guatemala	3.7
59	Guinea	9.5
60	Guinea-Bissau	0.2
61	Guyana	2.1
62	Haiti	18.7
63	Honduras	4.4
64	Hungary	3.3
65	Iceland	3.0
66	India	7.7
67	Indonesia	3.0
68	Iran	39.9
69	Iraq	-0.2
70	Ireland	0.9
71	Israel	0.8
72	Italy	0.6
73	Ivory Coast	-1.1
74	Jamaica	3.9
75	Japan	0.5
76	Jordan	0.8
77	Kazakhstan	NaN
78	Kenya	4.7
79	Kosovo	2.7
80	Kuwait	1.1
81	Kyrgyzstan	1.1
82	Laos	3.3
83	Latvia	2.8
84	Lebanon	3.0
85	Lesotho	5.2
86	Liberia	23.6
87	Libya	2.6
88	Lithuania	2.3
89	Luxembourg	1.7
90	Madagascar	5.6
91	Malawi	9.4
92	Malaysia	0.7
93	Mali	-1.7
94	Malta	1.6
95	Mauritania	2.3
96	Mexico	3.6
97	Moldova	4.8
98	Mongolia	7.3
99	Montenegro	0.4
100	Morocco	0.2
101	Mozambique	2.8
102	Myanmar	8.8
103	Namibia	3.7
104	Nepal	5.6
105	Netherlands	2.6
106	New Zealand	1.6
107	Nicaragua	5.4
108	Niger	-2.5
109	Nigeria	11.4
110	North Macedonia	0.8
111	Norway	2.2
112	Oman	0.1
113	Pakistan	10.6
114	Panama	-0.4
115	Papua New Guinea	3.6
116	Paraguay	2.8
117	Peru	2.1
118	Philippines	2.5
119	Poland	2.2
120	Portugal	0.3
121	Qatar	-0.7
122	Republic of Congo	2.2
123	Romania	3.8
124	Russia	4.5
125	Rwanda	3.3
126	Saudi Arabia	-2.1
127	Senegal	1.8
128	Serbia	1.8
129	Sierra Leone	14.8
130	Slovakia	2.7
131	Slovenia	1.6
132	Solomon Islands	1.6
133	Somalia	NaN
134	Somaliland	NaN
135	South Africa	4.1
136	South Korea	0.4
137	South Sudan	187.9
138	Spain	0.7
139	Sri Lanka	3.5
140	Sudan	51.0
141	Suriname	22.0
142	Sweden	1.8
143	Switzerland	0.4
144	Syria	36.7
145	Tajikistan	6.0
146	Tanzania	3.4
147	Thailand	0.7
148	Timor-Leste	1.0
149	Togo	0.7
150	Trinidad and Tobago	1.0
151	Tunisia	6.7
152	Turkey	15.2
153	Turkmenistan	NaN
154	Uganda	2.9
155	Ukraine	7.9
156	United Arab Emirates	-1.9
157	United Kingdom	1.7
158	United States	1.8
159	Uruguay	7.9
160	Uzbekistan	NaN
161	Vanuatu	2.8
162	Venezuela	254.9
163	Vietnam	2.8
164	Yemen	8.1
165	Zambia	9.2
166	Zimbabwe	10.6

continent = widgets.Dropdown(
 options=['North America', 'South America', 'Europe', 'Africa', 'Asia', 'Oceania'],
 value='North America',
 rows=6,
 description='Continent:'
 )
display(continent)

button_cont = widgets.Button(description='Display DataFrame')
display(button)

def button_click(b, cont):
    output = country_data[country_data['continent'] == cont]
    output = output[['name', 'inequality', 'wage_gap', 'social_mobility', 'poverty', 'inflation', 'unemployment']]
    display(output)

button_cont.on_click(button_click(0, continent.value))

	name	inequality	wage_gap	social_mobility	poverty	inflation	unemployment
9	Bahamas, The	NaN	NaN	NaN	NaN	2.5	14.4
13	Belize	NaN	NaN	NaN	NaN	NaN	7.8
26	Canada	0.303	17.594	76.1	0.118	1.9	9.5
32	Costa Rica	0.478	4.725	61.6	0.199	2.1	17.1
34	Cuba	NaN	NaN	NaN	NaN	NaN	3.9
40	Dominican Republic	NaN	NaN	NaN	NaN	1.8	8.9
43	El Salvador	NaN	NaN	47.4	NaN	0.1	7.0
58	Guatemala	NaN	NaN	43.5	NaN	3.7	4.7
62	Haiti	NaN	NaN	NaN	NaN	18.7	14.5
63	Honduras	NaN	NaN	43.5	NaN	4.4	9.4
74	Jamaica	NaN	NaN	NaN	NaN	3.9	8.4
96	Mexico	0.458	18.750	52.6	0.166	3.6	4.7
107	Nicaragua	NaN	NaN	NaN	NaN	5.4	5.8
114	Panama	NaN	NaN	51.4	NaN	-0.4	10.2
158	United States	0.390	18.471	70.4	0.178	1.8	8.3